Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Yohan Bonescki Gumiel"'
Autor:
Lucas Emanuel Silva e Oliveira, Ana Carolina Peters, Adalniza Moura Pucca da Silva, Caroline Pilatti Gebeluca, Yohan Bonescki Gumiel, Lilian Mie Mukai Cintho, Deborah Ribeiro Carvalho, Sadid Al Hasan, Claudia Maria Cabral Moro
Publikováno v:
Journal of Biomedical Semantics, Vol 13, Iss 1, Pp 1-19 (2022)
Abstract Background The high volume of research focusing on extracting patient information from electronic health records (EHRs) has led to an increase in the demand for annotated corpora, which are a precious resource for both the development and ev
Externí odkaz:
https://doaj.org/article/dca2a5a5934743c598bfb5786c86df86
Autor:
Everton Osnei Cesario, Yohan Bonescki Gumiel, Marcia Cristina Marins Martins, Viviane Maria de Carvalho Hessel Dias, Claudia Moro, Deborah Ribeiro Carvalho
Publikováno v:
Brazilian Archives of Biology and Technology, Vol 64, Iss spe (2021)
Abstract Sepsis is a systematic response to an infectious disease, being a concerning factor because of the increase in the mortality ratio for every delayed hour in the identification and start of patient’s treatment. Studies that aim to identify
Externí odkaz:
https://doaj.org/article/79a4b3a699d7407aad264b3bc34ef65e
Autor:
Claudia Maria Cabral Moro, Lucas Emanuel Silva e Oliveira, Yohan Bonescki Gumiel, Lucas Ferro Antunes de Oliveira, Deborah Ribeiro Carvalho
Publikováno v:
Research on Biomedical Engineering. 36:267-276
Natural language processing techniques are essential for unlocking patients’ data from electronic health records. An important NLP task is the ability to recognize morphosyntactic information from the texts, a process called part-of-speech (POS) ta
Autor:
Deborah Ribeiro Carvalho, Yohan Bonescki Gumiel, Cristiane Yumi Nakamura, Everton Osnei Cesario
Publikováno v:
Revista de Gestão em Sistemas de Saúde. 9:15-31
A sepse é uma inflamação generalizada com elevada morbidade e mortalidade, cujo reconhecimento e tratamento precoce são fatores essenciais para uma melhor qualidade de vida para o paciente; caso não seja identificada e tratada rapidamente, poder
Autor:
Yohan Bonescki Gumiel, Isabela Lee, Tayane Arantes Soares, Thiago Castro Ferreira, Adriana Pagano
Publikováno v:
Anais do XIII Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana (STIL 2021).
This study introduces novel data and models for the task of Sentiment Analysis in Portuguese texts about Diabetes Mellitus. The corpus contains 1290 posts retrieved from online health community forums in Portuguese and annotated by two annotators acc
Autor:
Emerson Cabrera Paraiso, Yohan Bonescki Gumiel, Claudia Maria Cabral Moro, João Vitor Andrioli de Souza, Elisa Terumi Rubel Schneider
Publikováno v:
CBMS
Electronic health records (EHRs) contain patient-related information formed by structured and unstructured data, a valuable data source for Natural Language Processing (NLP) in the healthcare domain. The contextual word embeddings and Transformer-bas
Autor:
Lucas Emanuel Silva e Oliveira, Mayara Aparecida Passaura da Luz, Yohan Bonescki Gumiel, Elisa Terumi Rubel Schneider, Claudia Maria Cabral Moro, Emerson Cabrera Paraiso
Publikováno v:
Intelligent Systems ISBN: 9783030916985
Question answering (QA) systems aim to answer human questions made in natural language. This type of functionality can be very useful in the most diverse application domains, such as the biomedical and clinical. Considering the clinical context, wher
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d753b1c4586671ceff8883ec8fa325e
https://doi.org/10.1007/978-3-030-91699-2_10
https://doi.org/10.1007/978-3-030-91699-2_10
Autor:
Vincent Claveau, Yohan Bonescki Gumiel, Natalia Grabar, Deborah Ribeiro Carvalho, Clément Dalloux, Claudia Maria Cabral Moro, Lucas Emanuel Silva e Oliveira
Publikováno v:
Natural Language Engineering
Natural Language Engineering, 2020, ⟨10.1017/S1351324920000352⟩
Natural Language Engineering, Cambridge University Press (CUP), 2020, ⟨10.1017/S1351324920000352⟩
Natural Language Engineering, 2020, ⟨10.1017/S1351324920000352⟩
Natural Language Engineering, Cambridge University Press (CUP), 2020, ⟨10.1017/S1351324920000352⟩
Automatic detection of negated content is often a prerequisite in information extraction systems in various domains. In the biomedical domain especially, this task is important because negation plays an important role. In this work, two main contribu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04c79697a19f1a36bc122a0351942b5c
https://hal.science/hal-03021033
https://hal.science/hal-03021033
Autor:
Julien Knafou, Elisa Terumi Rubel Schneider, Emerson Cabrera Paraiso, Lucas Ferro Antunes de Oliveira, Jenny Copara, Douglas Teodoro, João Vitor Andrioli de Souza, Yohan Bonescki Gumiel, Lucas Emanuel Silva e Oliveira, Claudia Maria Cabral Moro Barra
Publikováno v:
ClinicalNLP@EMNLP
Proceedings of the 3rd Clinical Natural Language Processing Workshop pp. 65-72
Proceedings of the 3rd Clinical Natural Language Processing Workshop pp. 65-72
With the growing number of electronic health record data, clinical NLP tasks have become increasingly relevant to unlock valuable information from unstructured clinical text. Although the performance of downstream NLP tasks, such as named-entity reco
Autor:
Lucas Emanuel Silva, E Oliveira, Yohan Bonescki, Gumiel, Arnon Bruno Ventrilho, Dos Santos, Lilian Mie Mukai, Cintho, Deborah Ribeiro, Carvalho, Sadid A, Hasan, Claudia Maria Cabral, Moro
Publikováno v:
Studies in health technology and informatics. 264
In this paper, we trained a set of Portuguese clinical word embedding models of different granularities from multi-specialty and multi-institutional clinical narrative datasets. Then, we assessed their impact on a downstream biomedical NLP task of Ur